Lightweight Networks for COVID-19 Detection from Chest X-Ray Images inside a Low-Tier Android Device
The efforts to inoculate majority of the population have been slower than expected and this is especially true for lower income countries. This problem has caused a lot of worries and further accentuates the importance of timely and effective mass testing considering the emergence of newer variants....
Saved in:
Main Authors: | Bacad, Dave Jammin A, Abu, Patricia Angela R |
---|---|
Format: | text |
Published: |
Archīum Ateneo
2022
|
Subjects: | |
Online Access: | https://archium.ateneo.edu/discs-faculty-pubs/357 https://doi.org/10.1109/TENCON55691.2022.9978124 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Ateneo De Manila University |
Similar Items
-
Detecting COVID-19 from Chest X-Ray Images using a Lightweight Deep Transfer Learning Model with Improved Contrast Enhancement Technique
by: Bacad, Dave Jammin A, et al.
Published: (2021) -
VEntNet: hybrid deep convolutional neural network model for automated multi-class categorization of chest X-rays
by: Sudarshan, Vidya K., et al.
Published: (2022) -
The debate on CXR utilization and interpretation is only just beginning: A Pro/Con Debate
by: Mehta, A.C., et al.
Published: (2016) -
Viral Pneumonia screening on chest X-rays using confidence-aware anomaly detection
by: ZHANG, Jianpeng, et al.
Published: (2022) -
The effectiveness of full-body EOS compared with conventional chest X-ray in preoperative evaluation of the chest for patients undergoing spine operations
by: Hey H.W.D., et al.
Published: (2020)